Intelligent acoustic detection of defective porcelain station post insulators

Lasalvia, L. A. B.; Florentine, Mary; Ferreira, Tarso Vilela; Germano, André Dantas; Costa, Edson G. da

doi:10.1109/icacact.2014.7223500

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…Measurement of electric field and voltage distribution on the insulators string, acoustic emission measurement, night vision camera, infrared thermography is used to improve the diagnostic of the insulator and reach a representative result. However, all of these techniques require qualified personnel who must be in contact with or near the insulator [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Sensing Method Using Multiple Quantities for Diagnostic of Insulators in Different Ambient Conditions

Dolník

Šárpataky

Kolcunová

et al. 2022

Sensors

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Insulators are one of the many components responsible for the reliability of electricity supply as part of transmission and distribution lines. Failure of the insulator can cause considerable economic problems that are much greater than the insulator cost. When the failure occurs on the transmission line, a large area can be without electricity supply or other transmission lines will be overloaded. Because of the consequences of the insulator’s failure, diagnostics of the insulator plays a significant role in the reliability of the power supply. Basic diagnostic methods require experienced personnel, and inspection requires moving in the field. New diagnostic methods require online measurement if it is possible. Diagnostic by measuring the leakage current flowing on the surface of the insulator is well known. However, many other quantities can be used as a good tool for diagnostics of insulators. We present in this article results obtained on the investigated porcelain insulators that are one of the most used insulation materials for housing the insulator’s core. Leakage current, dielectric loss factor, capacity, and electric charge are used as diagnostic quantities to investigate porcelain insulators in different pollution conditions and different ambient relative humidity. Pollution and humidity are the main factors that decrease the insulator´s electric strength and reliability.

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Section: Introductionmentioning

confidence: 99%

Sensing Method Using Multiple Quantities for Diagnostic of Insulators in Different Ambient Conditions

Dolník

Šárpataky

Kolcunová

et al. 2022

Sensors

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“…However, compared with equipment such as circuit breakers and gas-insulated switchgear, most of its transmission components are directly exposed and are eroded by environmental factors, resulting in frequent failures. Common faults include deformation and failure of transmission components [8], insufficient action [6][7][8][9][10], overheating of conductive circuits [10], damage to insulators [11], and secondary circuit faults. From 2008 to 2016, there were 357 faults reported by disconnectors with voltage levels of 126kV and above voltage class in Yunnan Power Grid, of which mechanical defects accounted for 55% of the total [11].…”

Section: Introductionmentioning

confidence: 99%

Research on mechanical state identification method of multi-type disconnectors based on difference curve and SVM

Yang

Wang

et al. 2023

J. Phys.: Conf. Ser.

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There are various types of high-voltage isolating switches and frequent mechanical defects, but it is difficult to meet engineering needs by detecting the mechanical state of a single isolating switch. Currently, most of the research only takes the GW4 disconnector as the research object, and the practicability of related diagnostic methods remains to be verified. In this paper, the difference curve is obtained as the sample to be identified by comparing the travel curve of the isolating switch to be diagnosed and its historical standard curve. With further elimination of the travel curve difference caused by the isolating switch model, extraction of the relevant time domain feature quantity, and combination of the support vector, the algorithm uses half of the data of each model in each state as the training sample and the other half of the data as the test sample, and the recognition accuracy rate is 100%. The GW4 and GW23 data are used as the training samples, the GW7 and GW36 data are used as the test samples, and the recognition accuracy is accurate. The rate was 87.5%. It is verified that the method of segmental extraction of difference curve features, combined with the support vector machine algorithm, can realize the intelligent identification of the mechanical state of different types of disconnectors, in which the degree of fault directly affects the spatial distribution of the samples and has a great impact on the accuracy of the identification results.

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“…The analysis is performed on insulators to identify contamination levels using radial basis function (RBF). A complete analysis for porcelain post insulators is presented [17] and also for polymer insulators [18] for identifying its degradation.…”

Section: Introductionmentioning

confidence: 99%

“…The improvement of feature extraction can also improve accuracy [17]. Using wavelet, the average accuracy for training is only 82.14%, while using Spectral Subband Centroid Vectors, the average accuracy is 98.63%.…”

Section: Introductionmentioning

confidence: 99%

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Stefenon

Branco

Nied

et al. 2020

IET Generation, Transmission & Distribution

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Intelligent acoustic detection of defective porcelain station post insulators

Cited by 8 publications

References 4 publications

Sensing Method Using Multiple Quantities for Diagnostic of Insulators in Different Ambient Conditions

Sensing Method Using Multiple Quantities for Diagnostic of Insulators in Different Ambient Conditions

Research on mechanical state identification method of multi-type disconnectors based on difference curve and SVM

Analysis of training techniques of ANN for classification of insulators in electrical power systems

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